Signal dispersion, such as echoes, ghosts, multipath and intersymbol interference, is an ever-present reality in communications systems. The severity of this problem varies with the system application and, at times, can render a system completely inoperative. For example, signal ghosts or echoes at levels which are merely objectional to the viewer of a conventional television signal can render a high-definition television (HDTV) signal unintelligible. Accordingly, cancellation or compensation for such dispersion cannot be ignored.
Ghosts in a television channel can be categorized as being either precursor or postcursor. A precursor ghost is one that precedes its associated transmitted signal while a postcursor ghost is one that succeeds its associated transmitted signal. FIG. 1 shows a typical ghost canceller structure 100 which includes a feedforward finite impulse response (FIR) filter 101 and an infinite impulse response (IIR) filter 102 in cascade. FIR filter 102 includes a feedback FIR filter 103 and combiner 104, the latter subtracting the output of feedback FIR filter 103 from the output of feedforward FIR filter 101. The feedforward FIR filter equalizes the main signal and any precursor ghosts while the IIR filter, also known as the feedback section, compensates for the one of more postcursor ghosts. The dispersion of the signal defines the required length or span of the feedback FIR filter and is the most difficult part of the ghost canceller structure to implement. While the exact position of any ghosts relative to an associated signal can vary from one application to the next, ghosts in a television channel are generally widely separated from one another and extend over a large time span. For example, the time interval between the furthest precursor and postcursor ghosts associated with the same transmitted signal can be 40 .mu.g seconds.
One prior art technique for implementing the feedback FIR filter in IIR filter 102, referred to as the full-span approach, is shown in FIG. 2. This approach involves implementing the feedback FIR filter using a data memory 201 and tap-weight coefficient store 202. In typical ghost cancellation applications, data memory 201 must have the capacity to store several hundred signal samples, and tap-weight coefficient store 202 must provide one tap-weight coefficient for each stored signal sample. At the incoming signal sample rate, each of the stored signal samples in data memory 201 must be multiplied by its associated tap-weight coefficient in data store 202 via multiplier 203 and the sum of these products coupled to combiner 104. While the full-span structure provides satisfactory ghost cancellation, it is very costly to implement since the incoming signal sample rate is high, e.g., 14.3 MHz, and many high-speed multiplications must be performed at this rate. In addition, the structure is inefficient since most of the tap-weight coefficients have a value of zero due to the wide time separation between ghosts.
FIG. 3 shows another prior art approach, referred to as the segmented-sparse technique, to implement the feedback FIR filter in IIR filter 102. This technique involves the use of variable delay random access memory segments 301-1 through 301-N which are inserted between a plurality of HR filters 302-1 through 302-N. The outputs of such filters are combined by summer 303. While this approach reduces the hardware required compared to the full-span approach, its rigid architectural structure still requires circuit overdesign to meet the required performance goals. For example, if the delay between adjacent ghosts is greater than the maximum delay provided by one memory segment, two or more such memory segments must be concatenated and use of the FIR filter disposed between such segments is lost. Alternatively, when the ghosts are closely-spaced, more than one FIR filter is required between adjacent memory segments and use of a number of memory segments will be lost. As a result, depending on the locations of the ghosts, there is often an underutilization of either FIR filters or memory segments with the segmented-sparse technique.
Accordingly, it would be extremely desirable if a more flexible ghost cancellation structure could be provided which fulfilled both the necessary performance and cost objectives.